[v1,1/3] mldev: add support for arbitrary shape dimensions

diff --git a/app/test-mldev/test_inference_common.c b/app/test-mldev/test_inference_common.c
index 418bf38be4c..6bda37b0fab 100644
--- a/app/test-mldev/test_inference_common.c
+++ b/app/test-mldev/test_inference_common.c
@@ -3,6 +3,7 @@ 
  */
 
 #include <errno.h>
+#include <math.h>
 #include <stdio.h>
 #include <unistd.h>
 
@@ -18,11 +19,6 @@ 
 #include "ml_common.h"
 #include "test_inference_common.h"
 
-#define ML_TEST_READ_TYPE(buffer, type) (*((type *)buffer))
-
-#define ML_TEST_CHECK_OUTPUT(output, reference, tolerance) \
-	(((float)output - (float)reference) <= (((float)reference * tolerance) / 100.0))
-
 #define ML_OPEN_WRITE_GET_ERR(name, buffer, size, err) \
 	do { \
 		FILE *fp = fopen(name, "w+"); \
@@ -763,9 +759,9 @@  ml_inference_validation(struct ml_test *test, struct ml_request *req)
 {
 	struct test_inference *t = ml_test_priv((struct ml_test *)test);
 	struct ml_model *model;
-	uint32_t nb_elements;
-	uint8_t *reference;
-	uint8_t *output;
+	float *reference;
+	float *output;
+	float deviation;
 	bool match;
 	uint32_t i;
 	uint32_t j;
@@ -777,89 +773,30 @@  ml_inference_validation(struct ml_test *test, struct ml_request *req)
 		match = (rte_hash_crc(model->output, model->out_dsize, 0) ==
 			 rte_hash_crc(model->reference, model->out_dsize, 0));
 	} else {
-		output = model->output;
-		reference = model->reference;
+		output = (float *)model->output;
+		reference = (float *)model->reference;
 
 		i = 0;
 next_output:
-		nb_elements =
-			model->info.output_info[i].shape.w * model->info.output_info[i].shape.x *
-			model->info.output_info[i].shape.y * model->info.output_info[i].shape.z;
 		j = 0;
 next_element:
 		match = false;
-		switch (model->info.output_info[i].dtype) {
-		case RTE_ML_IO_TYPE_INT8:
-			if (ML_TEST_CHECK_OUTPUT(ML_TEST_READ_TYPE(output, int8_t),
-						 ML_TEST_READ_TYPE(reference, int8_t),
-						 t->cmn.opt->tolerance))
-				match = true;
-
-			output += sizeof(int8_t);
-			reference += sizeof(int8_t);
-			break;
-		case RTE_ML_IO_TYPE_UINT8:
-			if (ML_TEST_CHECK_OUTPUT(ML_TEST_READ_TYPE(output, uint8_t),
-						 ML_TEST_READ_TYPE(reference, uint8_t),
-						 t->cmn.opt->tolerance))
-				match = true;
-
-			output += sizeof(float);
-			reference += sizeof(float);
-			break;
-		case RTE_ML_IO_TYPE_INT16:
-			if (ML_TEST_CHECK_OUTPUT(ML_TEST_READ_TYPE(output, int16_t),
-						 ML_TEST_READ_TYPE(reference, int16_t),
-						 t->cmn.opt->tolerance))
-				match = true;
-
-			output += sizeof(int16_t);
-			reference += sizeof(int16_t);
-			break;
-		case RTE_ML_IO_TYPE_UINT16:
-			if (ML_TEST_CHECK_OUTPUT(ML_TEST_READ_TYPE(output, uint16_t),
-						 ML_TEST_READ_TYPE(reference, uint16_t),
-						 t->cmn.opt->tolerance))
-				match = true;
-
-			output += sizeof(uint16_t);
-			reference += sizeof(uint16_t);
-			break;
-		case RTE_ML_IO_TYPE_INT32:
-			if (ML_TEST_CHECK_OUTPUT(ML_TEST_READ_TYPE(output, int32_t),
-						 ML_TEST_READ_TYPE(reference, int32_t),
-						 t->cmn.opt->tolerance))
-				match = true;
-
-			output += sizeof(int32_t);
-			reference += sizeof(int32_t);
-			break;
-		case RTE_ML_IO_TYPE_UINT32:
-			if (ML_TEST_CHECK_OUTPUT(ML_TEST_READ_TYPE(output, uint32_t),
-						 ML_TEST_READ_TYPE(reference, uint32_t),
-						 t->cmn.opt->tolerance))
-				match = true;
-
-			output += sizeof(uint32_t);
-			reference += sizeof(uint32_t);
-			break;
-		case RTE_ML_IO_TYPE_FP32:
-			if (ML_TEST_CHECK_OUTPUT(ML_TEST_READ_TYPE(output, float),
-						 ML_TEST_READ_TYPE(reference, float),
-						 t->cmn.opt->tolerance))
-				match = true;
-
-			output += sizeof(float);
-			reference += sizeof(float);
-			break;
-		default: /* other types, fp8, fp16, bfloat16 */
+		deviation =
+			(*reference == 0 ? 0 : 100 * fabs(*output - *reference) / fabs(*reference));
+		if (deviation <= t->cmn.opt->tolerance)
 			match = true;
-		}
+		else
+			ml_err("id = %d, element = %d, output = %f, reference = %f, deviation = %f %%\n",
+			       i, j, *output, *reference, deviation);
+
+		output++;
+		reference++;
 
 		if (!match)
 			goto done;
+
 		j++;
-		if (j < nb_elements)
+		if (j < model->info.output_info[i].nb_elements)
 			goto next_element;
 
 		i++;
diff --git a/drivers/ml/cnxk/cn10k_ml_model.c b/drivers/ml/cnxk/cn10k_ml_model.c
index 92c47d39baf..26df8d9ff94 100644
--- a/drivers/ml/cnxk/cn10k_ml_model.c
+++ b/drivers/ml/cnxk/cn10k_ml_model.c
@@ -366,6 +366,12 @@  cn10k_ml_model_addr_update(struct cn10k_ml_model *model, uint8_t *buffer, uint8_
 	addr->total_input_sz_q = 0;
 	for (i = 0; i < metadata->model.num_input; i++) {
 		if (i < MRVL_ML_NUM_INPUT_OUTPUT_1) {
+			addr->input[i].nb_dims = 4;
+			addr->input[i].shape[0] = metadata->input1[i].shape.w;
+			addr->input[i].shape[1] = metadata->input1[i].shape.x;
+			addr->input[i].shape[2] = metadata->input1[i].shape.y;
+			addr->input[i].shape[3] = metadata->input1[i].shape.z;
+
 			addr->input[i].nb_elements =
 				metadata->input1[i].shape.w * metadata->input1[i].shape.x *
 				metadata->input1[i].shape.y * metadata->input1[i].shape.z;
@@ -386,6 +392,13 @@  cn10k_ml_model_addr_update(struct cn10k_ml_model *model, uint8_t *buffer, uint8_
 				addr->input[i].sz_q);
 		} else {
 			j = i - MRVL_ML_NUM_INPUT_OUTPUT_1;
+
+			addr->input[i].nb_dims = 4;
+			addr->input[i].shape[0] = metadata->input2[j].shape.w;
+			addr->input[i].shape[1] = metadata->input2[j].shape.x;
+			addr->input[i].shape[2] = metadata->input2[j].shape.y;
+			addr->input[i].shape[3] = metadata->input2[j].shape.z;
+
 			addr->input[i].nb_elements =
 				metadata->input2[j].shape.w * metadata->input2[j].shape.x *
 				metadata->input2[j].shape.y * metadata->input2[j].shape.z;
@@ -412,6 +425,8 @@  cn10k_ml_model_addr_update(struct cn10k_ml_model *model, uint8_t *buffer, uint8_
 	addr->total_output_sz_d = 0;
 	for (i = 0; i < metadata->model.num_output; i++) {
 		if (i < MRVL_ML_NUM_INPUT_OUTPUT_1) {
+			addr->output[i].nb_dims = 1;
+			addr->output[i].shape[0] = metadata->output1[i].size;
 			addr->output[i].nb_elements = metadata->output1[i].size;
 			addr->output[i].sz_d =
 				addr->output[i].nb_elements *
@@ -426,6 +441,9 @@  cn10k_ml_model_addr_update(struct cn10k_ml_model *model, uint8_t *buffer, uint8_
 				   model->model_id, i, addr->output[i].sz_d, addr->output[i].sz_q);
 		} else {
 			j = i - MRVL_ML_NUM_INPUT_OUTPUT_1;
+
+			addr->output[i].nb_dims = 1;
+			addr->output[i].shape[0] = metadata->output2[j].size;
 			addr->output[i].nb_elements = metadata->output2[j].size;
 			addr->output[i].sz_d =
 				addr->output[i].nb_elements *
@@ -498,6 +516,7 @@  void
 cn10k_ml_model_info_set(struct rte_ml_dev *dev, struct cn10k_ml_model *model)
 {
 	struct cn10k_ml_model_metadata *metadata;
+	struct cn10k_ml_model_addr *addr;
 	struct rte_ml_model_info *info;
 	struct rte_ml_io_info *output;
 	struct rte_ml_io_info *input;
@@ -508,6 +527,7 @@  cn10k_ml_model_info_set(struct rte_ml_dev *dev, struct cn10k_ml_model *model)
 	info = PLT_PTR_CAST(model->info);
 	input = PLT_PTR_ADD(info, sizeof(struct rte_ml_model_info));
 	output = PLT_PTR_ADD(input, metadata->model.num_input * sizeof(struct rte_ml_io_info));
+	addr = &model->addr;
 
 	/* Set model info */
 	memset(info, 0, sizeof(struct rte_ml_model_info));
@@ -529,24 +549,25 @@  cn10k_ml_model_info_set(struct rte_ml_dev *dev, struct cn10k_ml_model *model)
 		if (i < MRVL_ML_NUM_INPUT_OUTPUT_1) {
 			rte_memcpy(input[i].name, metadata->input1[i].input_name,
 				   MRVL_ML_INPUT_NAME_LEN);
-			input[i].dtype = metadata->input1[i].input_type;
-			input[i].qtype = metadata->input1[i].model_input_type;
-			input[i].shape.format = metadata->input1[i].shape.format;
-			input[i].shape.w = metadata->input1[i].shape.w;
-			input[i].shape.x = metadata->input1[i].shape.x;
-			input[i].shape.y = metadata->input1[i].shape.y;
-			input[i].shape.z = metadata->input1[i].shape.z;
+			input[i].nb_dims = addr->input[i].nb_dims;
+			input[i].shape = addr->input[i].shape;
+			input[i].type = metadata->input1[i].model_input_type;
+			input[i].nb_elements = addr->input[i].nb_elements;
+			input[i].size =
+				addr->input[i].nb_elements *
+				rte_ml_io_type_size_get(metadata->input1[i].model_input_type);
 		} else {
 			j = i - MRVL_ML_NUM_INPUT_OUTPUT_1;
+
 			rte_memcpy(input[i].name, metadata->input2[j].input_name,
 				   MRVL_ML_INPUT_NAME_LEN);
-			input[i].dtype = metadata->input2[j].input_type;
-			input[i].qtype = metadata->input2[j].model_input_type;
-			input[i].shape.format = metadata->input2[j].shape.format;
-			input[i].shape.w = metadata->input2[j].shape.w;
-			input[i].shape.x = metadata->input2[j].shape.x;
-			input[i].shape.y = metadata->input2[j].shape.y;
-			input[i].shape.z = metadata->input2[j].shape.z;
+			input[i].nb_dims = addr->input[i].nb_dims;
+			input[i].shape = addr->input[i].shape;
+			input[i].type = metadata->input2[j].model_input_type;
+			input[i].nb_elements = addr->input[i].nb_elements;
+			input[i].size =
+				addr->input[i].nb_elements *
+				rte_ml_io_type_size_get(metadata->input2[j].model_input_type);
 		}
 	}
 
@@ -555,24 +576,25 @@  cn10k_ml_model_info_set(struct rte_ml_dev *dev, struct cn10k_ml_model *model)
 		if (i < MRVL_ML_NUM_INPUT_OUTPUT_1) {
 			rte_memcpy(output[i].name, metadata->output1[i].output_name,
 				   MRVL_ML_OUTPUT_NAME_LEN);
-			output[i].dtype = metadata->output1[i].output_type;
-			output[i].qtype = metadata->output1[i].model_output_type;
-			output[i].shape.format = RTE_ML_IO_FORMAT_1D;
-			output[i].shape.w = metadata->output1[i].size;
-			output[i].shape.x = 1;
-			output[i].shape.y = 1;
-			output[i].shape.z = 1;
+			output[i].nb_dims = addr->output[i].nb_dims;
+			output[i].shape = addr->output[i].shape;
+			output[i].type = metadata->output1[i].model_output_type;
+			output[i].nb_elements = addr->output[i].nb_elements;
+			output[i].size =
+				addr->output[i].nb_elements *
+				rte_ml_io_type_size_get(metadata->output1[i].model_output_type);
 		} else {
 			j = i - MRVL_ML_NUM_INPUT_OUTPUT_1;
+
 			rte_memcpy(output[i].name, metadata->output2[j].output_name,
 				   MRVL_ML_OUTPUT_NAME_LEN);
-			output[i].dtype = metadata->output2[j].output_type;
-			output[i].qtype = metadata->output2[j].model_output_type;
-			output[i].shape.format = RTE_ML_IO_FORMAT_1D;
-			output[i].shape.w = metadata->output2[j].size;
-			output[i].shape.x = 1;
-			output[i].shape.y = 1;
-			output[i].shape.z = 1;
+			output[i].nb_dims = addr->output[i].nb_dims;
+			output[i].shape = addr->output[i].shape;
+			output[i].type = metadata->output2[j].model_output_type;
+			output[i].nb_elements = addr->output[i].nb_elements;
+			output[i].size =
+				addr->output[i].nb_elements *
+				rte_ml_io_type_size_get(metadata->output2[j].model_output_type);
 		}
 	}
 }
diff --git a/drivers/ml/cnxk/cn10k_ml_model.h b/drivers/ml/cnxk/cn10k_ml_model.h
index 1f689363fc4..4cc0744891b 100644
--- a/drivers/ml/cnxk/cn10k_ml_model.h
+++ b/drivers/ml/cnxk/cn10k_ml_model.h
@@ -409,6 +409,12 @@  struct cn10k_ml_model_addr {
 
 	/* Input address and size */
 	struct {
+		/* Number of dimensions in shape */
+		uint32_t nb_dims;
+
+		/* Shape of input */
+		uint32_t shape[4];
+
 		/* Number of elements */
 		uint32_t nb_elements;
 
@@ -421,6 +427,12 @@  struct cn10k_ml_model_addr {
 
 	/* Output address and size */
 	struct {
+		/* Number of dimensions in shape */
+		uint32_t nb_dims;
+
+		/* Shape of input */
+		uint32_t shape[4];
+
 		/* Number of elements */
 		uint32_t nb_elements;
 
diff --git a/drivers/ml/cnxk/cn10k_ml_ops.c b/drivers/ml/cnxk/cn10k_ml_ops.c
index 656467d8918..e3faab81ba3 100644
--- a/drivers/ml/cnxk/cn10k_ml_ops.c
+++ b/drivers/ml/cnxk/cn10k_ml_ops.c
@@ -321,8 +321,8 @@  cn10k_ml_model_print(struct rte_ml_dev *dev, uint16_t model_id, FILE *fp)
 	fprintf(fp, "\n");
 
 	print_line(fp, LINE_LEN);
-	fprintf(fp, "%8s  %16s  %12s  %18s  %12s  %14s\n", "input", "input_name", "input_type",
-		"model_input_type", "quantize", "format");
+	fprintf(fp, "%8s  %16s  %12s  %18s  %12s\n", "input", "input_name", "input_type",
+		"model_input_type", "quantize");
 	print_line(fp, LINE_LEN);
 	for (i = 0; i < model->metadata.model.num_input; i++) {
 		if (i < MRVL_ML_NUM_INPUT_OUTPUT_1) {
@@ -335,12 +335,10 @@  cn10k_ml_model_print(struct rte_ml_dev *dev, uint16_t model_id, FILE *fp)
 			fprintf(fp, "%*s  ", 18, str);
 			fprintf(fp, "%*s", 12,
 				(model->metadata.input1[i].quantize == 1 ? "Yes" : "No"));
-			rte_ml_io_format_to_str(model->metadata.input1[i].shape.format, str,
-						STR_LEN);
-			fprintf(fp, "%*s", 16, str);
 			fprintf(fp, "\n");
 		} else {
 			j = i - MRVL_ML_NUM_INPUT_OUTPUT_1;
+
 			fprintf(fp, "%8u  ", i);
 			fprintf(fp, "%*s  ", 16, model->metadata.input2[j].input_name);
 			rte_ml_io_type_to_str(model->metadata.input2[j].input_type, str, STR_LEN);
@@ -350,9 +348,6 @@  cn10k_ml_model_print(struct rte_ml_dev *dev, uint16_t model_id, FILE *fp)
 			fprintf(fp, "%*s  ", 18, str);
 			fprintf(fp, "%*s", 12,
 				(model->metadata.input2[j].quantize == 1 ? "Yes" : "No"));
-			rte_ml_io_format_to_str(model->metadata.input2[j].shape.format, str,
-						STR_LEN);
-			fprintf(fp, "%*s", 16, str);
 			fprintf(fp, "\n");
 		}
 	}
diff --git a/lib/mldev/mldev_utils.c b/lib/mldev/mldev_utils.c
index d2442b123b8..ccd2c39ca89 100644
--- a/lib/mldev/mldev_utils.c
+++ b/lib/mldev/mldev_utils.c
@@ -86,33 +86,3 @@  rte_ml_io_type_to_str(enum rte_ml_io_type type, char *str, int len)
 		rte_strlcpy(str, "invalid", len);
 	}
 }
-
-void
-rte_ml_io_format_to_str(enum rte_ml_io_format format, char *str, int len)
-{
-	switch (format) {
-	case RTE_ML_IO_FORMAT_NCHW:
-		rte_strlcpy(str, "NCHW", len);
-		break;
-	case RTE_ML_IO_FORMAT_NHWC:
-		rte_strlcpy(str, "NHWC", len);
-		break;
-	case RTE_ML_IO_FORMAT_CHWN:
-		rte_strlcpy(str, "CHWN", len);
-		break;
-	case RTE_ML_IO_FORMAT_3D:
-		rte_strlcpy(str, "3D", len);
-		break;
-	case RTE_ML_IO_FORMAT_2D:
-		rte_strlcpy(str, "Matrix", len);
-		break;
-	case RTE_ML_IO_FORMAT_1D:
-		rte_strlcpy(str, "Vector", len);
-		break;
-	case RTE_ML_IO_FORMAT_SCALAR:
-		rte_strlcpy(str, "Scalar", len);
-		break;
-	default:
-		rte_strlcpy(str, "invalid", len);
-	}
-}
diff --git a/lib/mldev/mldev_utils.h b/lib/mldev/mldev_utils.h
index 5bc80204532..220afb42f0d 100644
--- a/lib/mldev/mldev_utils.h
+++ b/lib/mldev/mldev_utils.h
@@ -52,22 +52,6 @@  __rte_internal
 void
 rte_ml_io_type_to_str(enum rte_ml_io_type type, char *str, int len);
 
-/**
- * @internal
- *
- * Get the name of an ML IO format.
- *
- * @param[in] type
- *	Enumeration of ML IO format.
- * @param[in] str
- *	Address of character array.
- * @param[in] len
- *	Length of character array.
- */
-__rte_internal
-void
-rte_ml_io_format_to_str(enum rte_ml_io_format format, char *str, int len);
-
 /**
  * @internal
  *
diff --git a/lib/mldev/rte_mldev.h b/lib/mldev/rte_mldev.h
index fc3525c1ab5..6204df09308 100644
--- a/lib/mldev/rte_mldev.h
+++ b/lib/mldev/rte_mldev.h
@@ -863,47 +863,6 @@  enum rte_ml_io_type {
 	/**< 16-bit brain floating point number. */
 };
 
-/**
- * Input and output format. This is used to represent the encoding type of multi-dimensional
- * used by ML models.
- */
-enum rte_ml_io_format {
-	RTE_ML_IO_FORMAT_NCHW = 1,
-	/**< Batch size (N) x channels (C) x height (H) x width (W) */
-	RTE_ML_IO_FORMAT_NHWC,
-	/**< Batch size (N) x height (H) x width (W) x channels (C) */
-	RTE_ML_IO_FORMAT_CHWN,
-	/**< Channels (C) x height (H) x width (W) x batch size (N) */
-	RTE_ML_IO_FORMAT_3D,
-	/**< Format to represent a 3 dimensional data */
-	RTE_ML_IO_FORMAT_2D,
-	/**< Format to represent matrix data */
-	RTE_ML_IO_FORMAT_1D,
-	/**< Format to represent vector data */
-	RTE_ML_IO_FORMAT_SCALAR,
-	/**< Format to represent scalar data */
-};
-
-/**
- * Input and output shape. This structure represents the encoding format and dimensions
- * of the tensor or vector.
- *
- * The data can be a 4D / 3D tensor, matrix, vector or a scalar. Number of dimensions used
- * for the data would depend on the format. Unused dimensions to be set to 1.
- */
-struct rte_ml_io_shape {
-	enum rte_ml_io_format format;
-	/**< Format of the data */
-	uint32_t w;
-	/**< First dimension */
-	uint32_t x;
-	/**< Second dimension */
-	uint32_t y;
-	/**< Third dimension */
-	uint32_t z;
-	/**< Fourth dimension */
-};
-
 /** Input and output data information structure
  *
  * Specifies the type and shape of input and output data.
@@ -911,12 +870,18 @@  struct rte_ml_io_shape {
 struct rte_ml_io_info {
 	char name[RTE_ML_STR_MAX];
 	/**< Name of data */
-	struct rte_ml_io_shape shape;
-	/**< Shape of data */
-	enum rte_ml_io_type qtype;
-	/**< Type of quantized data */
-	enum rte_ml_io_type dtype;
-	/**< Type of de-quantized data */
+	uint32_t nb_dims;
+	/**< Number of dimensions in shape */
+	uint32_t *shape;
+	/**< Shape of the tensor */
+	enum rte_ml_io_type type;
+	/**< Type of data
+	 * @see enum rte_ml_io_type
+	 */
+	uint64_t nb_elements;
+	/** Number of elements in tensor */
+	uint64_t size;
+	/** Size of tensor in bytes */
 };
 
 /** Model information structure */
diff --git a/lib/mldev/version.map b/lib/mldev/version.map
index 0706b565be6..40ff27f4b95 100644
--- a/lib/mldev/version.map
+++ b/lib/mldev/version.map
@@ -51,7 +51,6 @@  INTERNAL {
 
 	rte_ml_io_type_size_get;
 	rte_ml_io_type_to_str;
-	rte_ml_io_format_to_str;
 	rte_ml_io_float32_to_int8;
 	rte_ml_io_int8_to_float32;
 	rte_ml_io_float32_to_uint8;